Machine Learning Cloud Infrastructure Lead
As an ML Cloud Infrastructure Technical Lead you will provide technical leadership for a growing team of cloud and machine learning engineers. The team is tasked with leading development of our data architecture, model training, deployment, and evaluation infrastructure. You will also take a leading role in development of model training services that provide optimized models and can be run by non-data scientists for use by both external and internal customers. You’ll build, maintain and improve data processing pipelines that process billions of data points and petabytes of data.
Additionally and specifically, guide the team in providing infrastructure services, starting with computational services: generate class predictions and embeddings by applying models to run IDs, morphometrics by applying morphometric models to run IDs, projections like UMAP, tSNE, PCA from embeddings, and extract clusters. Also help supply data services: cell data and metadata, obtain metadata about runs and datasets, model service, save and retrieve models and model metadata, image service to retrieve images from run IDs, label service to save and retrieve cell attributes (labels) by cell ID.
You’ll work with multiple interdisciplinary teams composed of data scientists, bioinformaticians, biologists and software engineers to help solve hard problems which improve biological research and, ultimately, health outcomes, across all of biology.
- This is an on-site position preferred but willing to consider exceptional remote candidates. Work from home as appropriate.
- Bachelors in computer science or equivalent
- 7 years' software development experience
- 5 years' experience leading data engineering teams of 5-10 engineers
- 5+ years' experience running medium to large/complex projects with multiple internal / external dependencies
- Familiarity with at least one deep learning framework, such as PyTorch, TensorFlow, or Caffe
- Proficient in Python
- Has built and deployed scalable cloud data architectures in a commercial setting
- Experienced in working with ETL pipelines
- Experienced in cloud providers such as GCP and AWS
- Strong analytical and problem solving skills
- Ability to understand and execute on the company’s mission and values
- Maintain a high degree of ethical standard and trustworthiness
- Strong technical written and oral communication skills
- 10+ years' software development experience
- 7+ years' experience in leading engineering teams
- A track record for delivering Machine Learning projects for a product
- Excellent written and verbal communication skills
- Strong and proactive communication, natural curiosity. Ambition to apply skills to a wide variety of fields
- Familiarity with latest data engineering ecosystems and ideally has contacts within the industry
- Be able and open to pick up new skills, work with 3rd party technologies and devices
- Experience with MLOps